Mild traumatic brain injury (TBI) represents one of the most significant health issues in VA and active duty military patients. Diagnosing and monitoring of TBI are major focuses of VA research. Mild (and some moderate) TBI can be difficult to diagnose because the injuries are generally not visible on conventional acute neuroimaging techniques (e.g., CT and MRI). Furthermore, conventional neuroimaging techniques have limited sensitivity to the physiological alterations due to TBI, and poor predictive utility for long-term outcome. Our preliminary study shows that neuronal tissues injured by trauma generate low frequency electromagnetic signals, decreased functional connectivity, and reduction of diffusion anisotropy. The proposed study will use integrated multi-modality neuroimaging approach involving Magnetoencephalography (MEG) and diffusion tensor imaging (DTI) in diagnosing and monitoring mild TBI. This approach has the potential of attaining higher sensitivity and specificity than conventional imaging techniques in detecting subtle neuronal injuries in mild TBI patients in VA and active duty military patients. There are three specific aims in the proposed study: Specific Aim 1 will investigate the diagnostic value of the integrated MEG-DTI approach in VA and active duty patients with mTBI by detecting neuronal injuries (loci of the injury as well as affected neuronal networks) not visible with conventional neuroimaging methods (e.g., CT and MRI). Our preliminary data show that pathological MEG slow-waves, reduced MEG functional connectivity, and reduced DTI anisotropy are characteristics of axonal injury due to tissue shearing and stretching in mTBI, with markedly better sensitivity than CT/MRI in diagnosing individual mild TBI patients. Specific Aim 2 studies the neurophysiological basis of the cognitive impairments using N-back working memory (WM) MEG task in active duty and VA patients with mild TBI. Specific Aim 3 of the present application will study the relationship between post-concussive symptoms, cognitive deficits as measured by neuropsychological exams, and the neuroimaging measurements with MEG and DTI in VA and active duty patients with mTBI. To achieve these aims, we propose to develop new imaging analysis tools: frequency-domain VESTAL for accurately localizing pathological MEG slow-waves; Dual-core Beamformer for reliably obtaining the neuronal networks with reduced functional connectivity using MEG under the condition of poor signal to noise ratio; and a platform for integrating the functional MEG findings in the gray-matter with structural DTI findings in the white-matter fiber tracts. The success of the proposed approach will not only greatly enhance our ability to diagnose mild TBI by detecting subtle neural injuries (e.g., loci and networks) that are invisible using conventional neuroimaging techniques, but also will provide the neuroimaging tools and software which can potentially be used as an objective evaluation method during pre- and post-intervention assessments of novel neuropharmacological and/or neuropsychological treatments for VA and active duty patients with TBI.